# Wikipedia in the Machine Relations Index

Canonical URL: https://machinerelations.ai/index/domains/wikipedia.org
Canonical domain: wikipedia.org
Source role: Academic and government source
Release mri_score_v2.0+2026-09-18+8fa38e54dd0a; methodology mri_score_v2.0; generated 2026-09-18; window 2026-05-10 to 2026-09-18; artifact 8fa38e54dd0a.

wikipedia.org appeared as a cited source in 192 of 15,782 monitored answer runs (1.22%) from 2026-05-10 to 2026-09-18.

## Overall Evidence

- Citation rate: 1.22%
- Cited runs: 192 of 15,782
- Days cited: 68 of 125
- Engine breadth: 6 observed engines (chatgpt, claude, gemini, google_ai_mode, google_ai_overviews, perplexity)
- Confidence: Confidence B
- Standing: #26 of 22,179 observed domains

## Observed Segments

| Category | Question shape | State | Cited runs | Observed runs | Run dates | Rate | Confidence | Standing |
|---|---|---|---:|---:|---:|---:|---|---|
| [AI Infrastructure](https://machinerelations.ai/index/categories/ai-infrastructure) | [Best tools](https://machinerelations.ai/index/categories/ai-infrastructure/best_x) | published | 3 | 77 | 7 | 3.90% | Unavailable | #72 of 204 |
| [AI Infrastructure](https://machinerelations.ai/index/categories/ai-infrastructure) | [How buyers choose](https://machinerelations.ai/index/categories/ai-infrastructure/how_choose) | published | 2 | 106 | 7 | 1.89% | Unavailable | #112 of 258 |
| [AI Infrastructure](https://machinerelations.ai/index/categories/ai-infrastructure) | [Comparisons](https://machinerelations.ai/index/categories/ai-infrastructure/x_vs_y) | published | 2 | 108 | 7 | 1.85% | Unavailable | #94 of 231 |
| [AI Security & Privacy](https://machinerelations.ai/index/categories/ai-security-privacy) | [Top lists](https://machinerelations.ai/index/categories/ai-security-privacy/top_list) | published | 3 | 106 | 7 | 2.83% | Unavailable | #96 of 313 |
| [AI Security & Privacy](https://machinerelations.ai/index/categories/ai-security-privacy) | [Comparisons](https://machinerelations.ai/index/categories/ai-security-privacy/x_vs_y) | published | 7 | 114 | 7 | 6.14% | Unavailable | #19 of 263 |
| [Consumer Finance](https://machinerelations.ai/index/categories/consumer-finance) | [How buyers choose](https://machinerelations.ai/index/categories/consumer-finance/how_choose) | published | 2 | 132 | 7 | 1.52% | Unavailable | #100 of 191 |
| [Consumer Health](https://machinerelations.ai/index/categories/consumer-health) | [Is it worth it](https://machinerelations.ai/index/categories/consumer-health/is_x_worth) | published | 1 | 130 | 7 | 0.77% | Unavailable | #209 of 213 |
| [Consumer Products](https://machinerelations.ai/index/categories/consumer-products) | [How buyers choose](https://machinerelations.ai/index/categories/consumer-products/how_choose) | published | 2 | 137 | 7 | 1.46% | Unavailable | #189 of 427 |
| [Consumer Products](https://machinerelations.ai/index/categories/consumer-products) | [Is it worth it](https://machinerelations.ai/index/categories/consumer-products/is_x_worth) | published | 1 | 136 | 7 | 0.74% | Unavailable | #224 of 228 |
| [Consumer Products](https://machinerelations.ai/index/categories/consumer-products) | [Top lists](https://machinerelations.ai/index/categories/consumer-products/top_list) | published | 1 | 131 | 7 | 0.76% | Unavailable | #374 of 380 |
| [Consumer Products](https://machinerelations.ai/index/categories/consumer-products) | [Comparisons](https://machinerelations.ai/index/categories/consumer-products/x_vs_y) | published | 2 | 131 | 7 | 1.53% | Unavailable | #148 of 268 |
| [Cybersecurity](https://machinerelations.ai/index/categories/cybersecurity) | [Best tools](https://machinerelations.ai/index/categories/cybersecurity/best_x) | published | 1 | 75 | 7 | 1.33% | Unavailable | #207 of 213 |
| [Cybersecurity](https://machinerelations.ai/index/categories/cybersecurity) | [How buyers choose](https://machinerelations.ai/index/categories/cybersecurity/how_choose) | published | 1 | 131 | 7 | 0.76% | Unavailable | #320 of 325 |
| [Cybersecurity](https://machinerelations.ai/index/categories/cybersecurity) | [News-driven citations](https://machinerelations.ai/index/categories/cybersecurity/news_topic) | published | 9 | 623 | 54 | 1.44% | Unavailable | #125 of 1,340 |
| [Cybersecurity](https://machinerelations.ai/index/categories/cybersecurity) | [Comparisons](https://machinerelations.ai/index/categories/cybersecurity/x_vs_y) | published | 1 | 107 | 7 | 0.93% | Unavailable | #185 of 189 |
| [Deep Tech & Hardware](https://machinerelations.ai/index/categories/deep-tech-hardware) | [Best tools](https://machinerelations.ai/index/categories/deep-tech-hardware/best_x) | published | 3 | 121 | 7 | 2.48% | Unavailable | #104 of 328 |
| [Deep Tech & Hardware](https://machinerelations.ai/index/categories/deep-tech-hardware) | [How buyers choose](https://machinerelations.ai/index/categories/deep-tech-hardware/how_choose) | published | 8 | 130 | 7 | 6.15% | Unavailable | #24 of 195 |
| [Deep Tech & Hardware](https://machinerelations.ai/index/categories/deep-tech-hardware) | [Is it worth it](https://machinerelations.ai/index/categories/deep-tech-hardware/is_x_worth) | published | 12 | 105 | 7 | 11.43% | Unavailable | #8 of 181 |
| [Deep Tech & Hardware](https://machinerelations.ai/index/categories/deep-tech-hardware) | [Problem-first research](https://machinerelations.ai/index/categories/deep-tech-hardware/problem_first) | published | 1 | 104 | 7 | 0.96% | Unavailable | #155 of 157 |
| [Deep Tech & Hardware](https://machinerelations.ai/index/categories/deep-tech-hardware) | [Top lists](https://machinerelations.ai/index/categories/deep-tech-hardware/top_list) | published | 7 | 106 | 7 | 6.60% | Unavailable | #23 of 279 |
| [Deep Tech & Hardware](https://machinerelations.ai/index/categories/deep-tech-hardware) | [Comparisons](https://machinerelations.ai/index/categories/deep-tech-hardware/x_vs_y) | published | 4 | 105 | 7 | 3.81% | Unavailable | #51 of 171 |
| [Education & Training](https://machinerelations.ai/index/categories/education-training) | [Problem-first research](https://machinerelations.ai/index/categories/education-training/problem_first) | published | 1 | 100 | 7 | 1.00% | Unavailable | #225 of 229 |
| [Emergent Prosumer](https://machinerelations.ai/index/categories/emergent-prosumer) | [Problem-first research](https://machinerelations.ai/index/categories/emergent-prosumer/problem_first) | published | 2 | 101 | 7 | 1.98% | Unavailable | #83 of 162 |
| [Enterprise Software](https://machinerelations.ai/index/categories/enterprise-software) | [News-driven citations](https://machinerelations.ai/index/categories/enterprise-software/news_topic) | published | 12 | 596 | 53 | 2.01% | Unavailable | #72 of 1,375 |
| [Enterprise Software](https://machinerelations.ai/index/categories/enterprise-software) | [Problem-first research](https://machinerelations.ai/index/categories/enterprise-software/problem_first) | published | 1 | 106 | 7 | 0.94% | Unavailable | #253 of 258 |
| [Family Software](https://machinerelations.ai/index/categories/family-software) | [Top lists](https://machinerelations.ai/index/categories/family-software/top_list) | published | 3 | 108 | 7 | 2.78% | Unavailable | #78 of 195 |
| [Family Software](https://machinerelations.ai/index/categories/family-software) | [Comparisons](https://machinerelations.ai/index/categories/family-software/x_vs_y) | published | 1 | 108 | 7 | 0.93% | Unavailable | #101 of 101 |
| [Fintech](https://machinerelations.ai/index/categories/fintech) | [News-driven citations](https://machinerelations.ai/index/categories/fintech/news_topic) | published | 9 | 616 | 53 | 1.46% | Unavailable | #132 of 1,531 |
| [Fintech](https://machinerelations.ai/index/categories/fintech) | [Top lists](https://machinerelations.ai/index/categories/fintech/top_list) | published | 4 | 102 | 7 | 3.92% | Unavailable | #49 of 200 |
| [Healthcare Services](https://machinerelations.ai/index/categories/healthcare-services) | [Best tools](https://machinerelations.ai/index/categories/healthcare-services/best_x) | collecting | 1 | 101 | 6 | Unavailable | Unavailable | Collecting observations; no mature rank |
| [Healthcare Services](https://machinerelations.ai/index/categories/healthcare-services) | [Is it worth it](https://machinerelations.ai/index/categories/healthcare-services/is_x_worth) | collecting | 1 | 101 | 6 | Unavailable | Unavailable | Collecting observations; no mature rank |
| [Healthcare Services](https://machinerelations.ai/index/categories/healthcare-services) | [News-driven citations](https://machinerelations.ai/index/categories/healthcare-services/news_topic) | published | 11 | 613 | 53 | 1.79% | Unavailable | #84 of 1,264 |
| [HR & Talent](https://machinerelations.ai/index/categories/hr-talent) | [News-driven citations](https://machinerelations.ai/index/categories/hr-talent/news_topic) | published | 16 | 608 | 53 | 2.63% | Unavailable | #54 of 1,249 |
| [HR & Talent](https://machinerelations.ai/index/categories/hr-talent) | [Problem-first research](https://machinerelations.ai/index/categories/hr-talent/problem_first) | collecting | 1 | 65 | 4 | Unavailable | Unavailable | Collecting observations; no mature rank |
| [iGaming & Betting](https://machinerelations.ai/index/categories/igaming-betting) | [Best tools](https://machinerelations.ai/index/categories/igaming-betting/best_x) | collecting | 1 | 35 | 2 | Unavailable | Unavailable | Collecting observations; no mature rank |
| [Legacy News Topics](https://machinerelations.ai/index/categories/legacy-unmapped) | [News-driven citations](https://machinerelations.ai/index/categories/legacy-unmapped/news_topic) | published | 38 | 2,138 | 54 | 1.78% | Unavailable | #55 of 4,025 |
| [Martech & Advertising](https://machinerelations.ai/index/categories/martech-advertising) | [News-driven citations](https://machinerelations.ai/index/categories/martech-advertising/news_topic) | published | 17 | 602 | 53 | 2.82% | Unavailable | #55 of 1,244 |

## Citation

Wikipedia (wikipedia.org), 1.22% citation rate, 192 of 15,782 monitored answer runs, 2026-05-10 to 2026-09-18, mri_score_v2.0, mri_score_v2.0+2026-09-18+8fa38e54dd0a, https://machinerelations.ai/index/domains/wikipedia.org.

## Public Boundary

The public dataset reports citation rates, rankings, and evidence counts. It excludes internal query identifiers, raw cited URLs, and answer-engine provider payloads. MRI measures observed root-domain citations in monitored prompts; it does not measure all AI answers, recommendation quality, website traffic, or commercial performance. A citation does not prove source support, and MRI confidence is not an Answer-Source Fidelity grade.

## Related Sources

- [Machine Relations Index](https://machinerelations.ai/index)
- [Public JSON artifact](https://machinerelations.ai/data/machine-relations-index.json)
- [Release manifest](https://machinerelations.ai/data/mri-release-manifest.json)
- [AuthorityTech publication intelligence projection](https://authoritytech.io/publications.md) — Practitioner projection derived from the neutral Machine Relations Index. It is not source evidence, citation provenance, or sameAs identity for the neutral dataset.